Nvidia’s new technique cuts LLM reasoning costs by 8x without losing accuracy

Nvidia researchers developed dynamic memory sparsification (DMS), a technique that compresses the KV cache in large language models by up to 8x while maintaining reasoning accuracy — and it can be ...

z.ai's open source GLM-5 achieves record low hallucination rate and leverages new RL 'slime' technique

The latest in z.ai's ongoing and continually impressive GLM series, it retains an open source MIT License — perfect for enterprise deployment – and, in one of several notable achievements, achieves a ...
Devdiscourse

Hybrid AI can reduce failures and energy use in manufacturing robots

The research, titled AI-Driven Hybrid Deep Learning and Swarm Intelligence for Predictive Maintenance of Smart Manufacturing Robots in Industry 4.0 and published in Electronics, introduces an AI ...
IEEE

Research on vehicle path planning algorithm for intelligent garage based on deep learning

Abstract: In this paper, a deep learning-based vehicle path planning algorithm for smart garages is proposed. Firstly, the research background of intelligent garage vehicle path planning and the ...
IEEE

Accurate Metaphase Chromosome Classification Using Faster R-CNN and Deep LSTM Integration

Abstract: The precise classification of metaphase chromosomes is essential for cytogenetic analysis, facilitating the detection of genetic diseases and anomalies. This paper introduces an improved ...